Instructions to use djelia/bm-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djelia/bm-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="djelia/bm-xlm-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("djelia/bm-xlm-roberta-base") model = AutoModelForMaskedLM.from_pretrained("djelia/bm-xlm-roberta-base") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an 11M words Bambara dataset. It achieves the following results on the evaluation set:
- Loss: 1.1160
- Accuracy: 0.7599
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Model tree for djelia/bm-xlm-roberta-base
Base model
FacebookAI/xlm-roberta-base